Image and video enhancement processes usually contain two conflicting tasks—noise reduction and details enhancement. The noise reduction task involves attenuating high frequency components, while the details enhancement task is performed by increasing high and mid frequency elements of an image. Hence, some linear approaches for reconstructing images or video sequences that have been affected by blurring and by additive noise have very poor performance. The more sophisticated adaptive approaches are effective but are more computationally demanding and are difficult to implement in real time.
Thus, there is a continuing need for a method for image and video enhancement that overcomes the shortcomings of the prior art.